This course introduces the principles of data representation, summarisation and presentation with particular emphasis on the use of graphics. The course will use the R Language in a modern computing environment. Topics to be discussed include:

·        Data representation; examples of good and bad graphics; principles of graphic construction; some pitfalls to be avoided; presentation graphics.

·        Graphics environments; interactive graphics; windows; linked windows; graphics objects.

·        Statistical graphics; stem and leaf plots, box plots, histograms; smoothing histograms; quantile-quantile plots; representing multivariate data; scatterplots; clustering; stars and faces; dynamic graphics including data rotation and brushing.

·        Relationships between variables; smoothing scatterplots; simple regression; modelling and diagnostic plots; exploring surfaces; contour plots and perspective plots; multiple regression; relationships in time and space; time series modelling and diagnostic plots.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Demonstrate detailed knowledge of the R statistical computing language, particularly graphical capabilities.
2. Explain in detail and be able to apply the principles of good data representation.
3. Explain in detail and be able to use various graphics environments, interactive graphics and graphics objects.
4. Construct graphical representations of one dimensional data.
5. Construct graphical representations for multivariate data including scatterplots, and dynamic graphics.
6. Use diagnostic plots when conducting statistical modelling to explore and refine statistical models for data, including detailed explanations of such use.
7. Construct and interpret graphical displays for dependent data.

Research-Led Teaching

This course builds upon the foundation in statistical thinking and evidence-based logic that you have acquired from previous statistics courses. The course contents and activities are designed to help you learn, apply and hone this foundation to prepare yourself for life in the workforce. Course contents and activities heavily involve statistical computing with R interfaced through R Studio. Additional materials (e.g. news reports, journal publications) will be discussed as examples and case studies in which research questions relevant to the course are tackled. 

Required Resources

Computing equipment during non-intensive weeks:

• You must make your own arrangements to purchase such equipment or to access ANU on-campus computers which are preloaded with course-relevant software R and Rstudio (free to download by clicking the links). More instructions about the software can be found on Wattle.
• Using a tablet (e.g., iPad, Android tablets) for course-related computing is possible via a cloud computing account. See the Wattle course page for instructions to obtain complimentary NeCTAR cloud computing accounts and course-relevant software. 

Recommended Resources

• The Guardian’s unofficial guide to “Studying online: seven ways to stay motivated.”
• Other recommended resources will be listed on the Wattle course page. 

Staff Feedback

Feedback from the teaching staff will aim to facilitate the learner's ongoing self assessment of his/her progress in achieving the learning objectives of the course. There are several ways to get feedback from the teaching staff:

(a) to benefit all the students, teaching staff strongly suggests the learners post course-related question publicly on the discussion forum of Wattle so that the teaching staff can reply those questions publicly.

(b) those students who have private things to discuss can email the teaching staff for consultation.

(c) students can also make an appointment by email to schedule a face-to-face consultation on campus or online consultation by Zoom or Skype.

In order to safeguard student privacy, staff members need to be sure that they are dealing with the right student, therefore course- related messages sent from non-ANU email accounts will be ignored.

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Pre-intensive period: March 11 - Apr 7 Introduction to R Representing and comparing distributions Relationship between two variables, scatterplot smoothing, simple linear models  Students watch recorded videos and self study additional learning materials published on Wattle. Campus attendance is not required.	Self assessment in RAssignment 1 (40%):available on: Monday April 1 2024due date: Monday April 15 2024
2	Intensive period: Apr 8 - Apr 12Daily Lecture + Tutorial: Review Relationship between several variables, multiple linear regression, model diagnostics, variable selection Campus attendance is recommended but not mandatory during the intensive period. Some students cannot be in Canberra, others have work obligations or health concerns. If you are one of these students, it is possible to complete the intensive period online. Students will work alone and in groups to analyse data sets and complete tasks. The lecturer will be available in the allocated computer labs to summarise video lectures, discuss topics and assist with questions. Students may work with their group remotely or on campus in the allocated computer lab with the lecturer. If working remotely, each group will have to book an online appointment with the lecturer to discuss progress and ask questions. The intensive period lab sessions or online group discussions won't be recorded. All lectures and tutorials are pre-recorded and available online.	Watch video materials and analyse class data sets with groups or alone. Join lab discussions with the lecturer to discuss what you have learned in each video. Work on assessment items.
3	Post-intensive period: Apr 13 - May 10 Review Summary of graphical construction  Students watch recorded videos and self study additional learning materials published on Wattle. Campus attendance is not required.	Assignment 2 (60%): available on Monday April 15 2024 due on Friday May 10 2024 (class end date)

Tutorial Registration

There are no tutorials for this course.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Assignment 1	40 %	15/04/2024	29/04/2024	1,2,3,4,5
Assignment 2	60 %	10/05/2024	03/06/2024	1,2,3,4,5,6,7

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Guideline and General Information 
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Students are recommended to be on campus in Canberra during the one-week intensive period but this will not be mandatory. Outside of the one-week intensive period, students are expected to use the materials available on Wattle to learn on their own. It is advised to regularly check Wattle for updated information. The teaching format will be regular in-person classroom discussion labs during the intensive period. Remote students may be able to schedule check-ins during this week via Zoom. The labs will not be recorded.

Assessment Task 1

Assignment 1

Details: Students are expected to complete the assignment individually. This assignment is designed to cover topics from the pre-intensive period. The assignment will require students to graphically explore a data set in order to uncover interesting and unique insights using graphical techniques learned during the pre-intensive period. Marks will be awarded for useful and unique insights uncovered using the graphical techniques learned through the pre-intensive period. The graphical exploration will be presented in a short report and the assignment will specify a page limit. Students will be expected to use RStudio to analyse the data set and construct the graphics. The assignment will be released on Monday April 1 by 9am.

Due date: Monday April 15 by 11:59pm. 

Value: 40%

Assessment Task 2

Assignment 2

Details:

Students are expected to complete the assignment individually. Assignment 2 will consist of two parts:

Part A. (20% = 4*5%) Communication Graphics:  A collection of four statistical graphics with written comments on each graphic. These graphics should be collected during the semester from published work (eg. journal articles, books, newspapers, websites, social media etc). Credit will be given for interesting graphics that uniquely convey a statistical message, either poorly or well. In addition to including a copy of the graphic itself, you should document the source of the graphic (title of article, authors, page numbers, website or source link etc.) and clearly communicate your analysis of the graphic. Your analysis should synthesise why you chose the graphic, with the statistical message it wishes to convey; how it has effectively communicated this statistical message or not - ie the graphics strengths, weaknesses and how the audience is likely to interpret the graphic. Your discussion may also include a redrawn or improved version of the graphic or a summary of how it should have been constructed so that the audience interprets the statistical message correctly.

Part B. (40%) Analysis Graphics: This part will focus on a topic that utilises the graphical tools you have learned in the course to analyse data.

Assignment 2 will be released on Monday April 15 by 5pm.

Due date: Friday May 10 by 11:59pm. 

Value: 60%

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Each assignment must be submitted as a single electronic file using Turnitin within the course Wattle site. Each of these assessments will require both statistical computing via R Studio and mathematical derivations (either handwritten or typeset using R Studio). If submitting handwritten mathematical derivations, ensure that your handwriting is legible, and scan the derivations (e.g., by using your smartphone camera) to be incorporated into your single electronic file. Prior to submission, you should practice using the Turnitin system here. Students can upload draft versions to the designated Turnitin web link on the Wattle course page, and change those drafts every 24 hours up until the due date.

Submissions outside of the designated Turnitin web link and/or after the due date will be ignored.

Hardcopy Submission

Assessment submission for this course will be online (see above).

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Returning Assignments

Graded assignments should be available via Turnitin within 14 days after the due date. Written feedback will be published on Wattle.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Resubmission of assessments is not allowed under any circumstance.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Access and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students